Illustrating error in a temperature distribution map

ABSTRACT

An apparatus acquires signals from thermal sensors on a probe and performs a first interpolation or a first extrapolation between temperatures determined from the signals based on the spatial locations of the thermal sensors to produce a temperature spatial distribution map, determines there is at least one malfunctioning thermal sensor, and assigns the malfunctioning thermal sensors a first arbitrary temperature and the correctly operating thermal sensors a second arbitrary temperature. The apparatus performs a second interpolation or a second extrapolation between the first arbitrary temperature and the second arbitrary temperatures based on the spatial locations of the thermal sensors so as to produce a spatial distribution of arbitrary temperatures, selects a section of the spatial distribution of arbitrary temperatures as having erroneous results to produce an error distribution map and superimposes graphically the error distribution map on the displayed temperature distribution map displayed on the screen.

FIELD OF THE INVENTION

The present invention relates generally to distribution maps, andspecifically to illustrating errors in maps of temperature distribution.

BACKGROUND OF THE INVENTION

It is advantageous to display information derived from measurements madeduring a surgical procedure graphically, so as to aid those performingthe procedure to quickly comprehend the measurements. A number of priorart references address this subject. For example:

US Patent Application 2015/0112149, to Govari et al., whose disclosureis incorporated herein by reference, describes a method for displayinginformation, including receiving measurements, with respect to aninvasive probe inside a body of a subject, of probe parametersconsisting of a force exerted by the probe on tissue of the subject andtemperatures measured by sensors of the probe.

U.S. Pat. No. 8,986,217 to Boese et al., whose disclosure isincorporated herein by reference, describes a mapping catheter fordetermination of data of an area of an organ embodied as a flat surface,especially of the heart. The data is to be presented graphically, withat least one thermosensor essentially aligned in the direction of thelongitudinal axis of the mapping catheter.

US Patent Application 2014/0171821, to Govari et al., whose disclosureis incorporated herein by reference, describes a medical probe thatincludes an insertion tube having a distal end configured for insertioninto a body of a patient. A plurality of temperature sensors are mountedwithin a conductive cap of the probe, and the disclosure states that thetemperature readings of the sensors can be combined and interpolated togive a map of temperature over the area of the probe tip.

Documents incorporated by reference in the present patent applicationare to be considered an integral part of the application except that, tothe extent that any terms are defined in these incorporated documents ina manner that conflicts with definitions made explicitly or implicitlyin the present specification, only the definitions in the presentspecification should be considered.

SUMMARY OF THE INVENTION

In one embodiment, an apparatus includes a probe in contact with abiological tissue, the probe having a plurality of thermal sensors, anda processor configured to acquire signals, indicative of temperatures atrespective spatial locations in the biological tissue, from theplurality of thermal sensors, perform a first interpolation or a firstextrapolation between temperatures determined from the signals based onthe spatial locations of the thermal sensors so as to produce atemperature spatial distribution map, display the temperature spatialdistribution map on a screen, determine that there is at least onemalfunctioning thermal sensor of the plurality of thermal sensors, andthat remaining thermal sensors of the plurality of thermal sensors arecorrectly operating thermal sensors, and assign the at least onemalfunctioning thermal sensor a first arbitrary temperature and each ofthe correctly operating thermal sensors a second arbitrary temperature.In one embodiment, in the case of performing the first interpolation,the processor is configured to perform a second interpolation andbetween the first arbitrary temperature and the second arbitrarytemperatures based on the spatial locations of the thermal sensors so asto produce a spatial distribution of arbitrary temperatures. In oneembodiment, in the case of performing the first extrapolation, theprocessor is configured to perform a second extrapolation between thefirst arbitrary temperature and the second arbitrary temperatures basedon the spatial locations of the thermal sensors so as to produce aspatial distribution of arbitrary temperatures. In one embodiment, theprocessor is configured to select a section of the spatial distributionof arbitrary temperatures as having erroneous results to produce anerror distribution map and superimpose graphically the errordistribution map on the displayed temperature distribution map displayedon the screen.

In one embodiment, a method includes:

acquiring signals, indicative of temperatures at respective locations ina biological tissue, from a plurality of thermal sensors mounted on aprobe in contact with the tissue;

interpolating between the temperatures so as to produce a temperaturedistribution map;

displaying the temperature distribution map on a screen;

determining that at least one of the thermal sensors is a malfunctioningthermal sensor, and that remaining thermal sensors of the plurality arecorrectly operating;

assigning the at least one malfunctioning thermal sensor a firstarbitrary temperature and the correctly operating thermal sensors secondarbitrary temperatures;

interpolating between the first and second arbitrary temperatures so asto produce an error distribution map indicative of a suspect portion ofthe temperature distribution map; and

superimposing graphically the error distribution map on the displayedtemperature distribution map.

Typically, interpolating between the temperatures includes using apredetermined method of interpolation and extrapolation, andinterpolating between the first and second arbitrary temperaturesincludes using the predetermined method of interpolation andextrapolation.

Alternatively, interpolating between the temperatures includes using afirst predetermined method of interpolation and extrapolation, andinterpolating between the first and second arbitrary temperaturesincludes using a second predetermined method of interpolation andextrapolation, different from the first predetermined method.

In a disclosed embodiment the error distribution map includes a regionenclosed by an isotherm generated by the interpolating between the firstand second arbitrary temperatures.

In a further disclosed embodiment the error distribution map is at leastpartially transparent so that a region of the temperature distributionmap underlying the error distribution map is visible.

In a yet further disclosed embodiment the error distribution map isdifferentiated visually from the temperature distribution map.

Typically the error distribution map is a subset of the temperaturedistribution map.

In an alternative embodiment the biological tissue consists of amyocardium, and the signals are acquired during ablation of themyocardium.

In a further alternative embodiment determining that the at least one ofthe thermal sensors is the malfunctioning thermal sensor consists ofregistering that a temperature indicated by the at least one of thethermal sensors is outside a preset acceptable range of temperatures.

In a yet further alternative embodiment the error distribution map andthe displayed temperature distribution map are two dimensional maps.Alternatively, the error distribution map and the displayed temperaturedistribution map are three dimensional maps.

There is further provided, according to an embodiment of the presentinvention embodiment, apparatus, including:

a probe, in contact with a biological tissue and having a plurality ofthermal sensors; and

a processor configured to:

acquire signals, indicative of temperatures at respective locations inthe biological tissue, from the plurality of thermal sensors,

interpolate between the temperatures so as to produce a temperaturedistribution map,

display the temperature distribution map on a screen.

determine that at least one of the thermal sensors is a malfunctioningthermal sensor, and that remaining thermal sensors of the plurality arecorrectly operating,

assign the at least one malfunctioning thermal sensor a first arbitrarytemperature and the correctly operating thermal sensors second arbitrarytemperatures,

interpolate between the first and second arbitrary temperatures so as toproduce an error distribution map indicative of a suspect portion of thetemperature distribution map, and

superimpose graphically the error distribution map on the displayedtemperature distribution map.

There is further provided, according to an embodiment of the presentinvention, a method, including:

acquiring signals, indicative of respective metrics at respectivelocations in a biological tissue, from at least one sensor mounted on aprobe in proximity with the tissue;

interpolating between the metrics so as to produce a metric distributionmap;

displaying the metric distribution map on a screen;

determining that at least one of the signals is indicative of anincorrect metric value, and that remaining signals are indicative ofcorrect metric values;

assigning the at least one of the signals a first arbitrary metric valueand the remaining signals second arbitrary metric values;

interpolating between the first and second arbitrary metric values so asto produce an error distribution map indicative of a suspect portion ofthe metric distribution map; and

superimposing graphically the error distribution map on the displayedmetric distribution map.

In a disclosed embodiment the biological tissue includes a heart, andthe metric includes a local activation time of the heart.

The error distribution map and the metric distribution map may bethree-dimensional maps.

In a further disclosed embodiment the incorrect metric value conflictswith an expected metric value determined in response to the correctmetric values.

In a yet further disclosed embodiment the at least one of the signalsprovides insufficient information for determining a correct metricvalue.

The present disclosure will be more fully understood from the followingdetailed description of the embodiments thereof, taken together with thedrawings, in which:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of an invasive medical procedure,according to an embodiment of the present invention;

FIGS. 2A, 2B, and 2C schematically illustrate a distal end of a probe,according to an embodiment of the present invention;

FIGS. 3A and 3B are schematic diagrams illustrating the spatialdistribution of temperature in the vicinity of the distal end, accordingto an embodiment of the present invention;

FIG. 4 is a flowchart of steps followed by a processor, according to anembodiment of the present invention;

FIGS. 5A and 5B schematically illustrate a 3D and a 2D errordistribution map, according to an embodiment of the present invention;and

FIGS. 6A and 6B schematically illustrate an implementation of theflowchart of FIG. 4, according to an embodiment of the presentinvention.

DETAILED DESCRIPTION OF EMBODIMENTS Overview

In an invasive surgical procedure a catheter or probe with multiplethermal sensors at the distal tip may be used to generate a temperaturedistribution map for the vicinity of the tip. In prior art systems, ifone or more of the sensors malfunctions, such a malfunction may benotified, for example by lighting a warning light, but the map is notaltered to indicate the malfunction.

Embodiments of the present disclosure provide a remedy if this problemoccurs during a procedure, by incorporating a “suspect region” into thedistribution map. Initially, signals, indicative of temperatures atrespective locations in a biological tissue, are acquired from aplurality of thermal sensors mounted on a probe in contact with thetissue. A temperature distribution map is formed by interpolating andextrapolating between the temperatures, and the map is displayed on ascreen.

At some stage in the procedure it is determined that at least one of thethermal sensors is a malfunctioning thermal sensor, while the remainingthermal sensors of the plurality are correctly operating. (Thedetermination may be made, for example, by finding that themalfunctioning sensor gives a reading outside an acceptable range ofreadings.) The at least one malfunctioning thermal sensor is assigned afirst arbitrary temperature and the correctly operating thermal sensorsare assigned second arbitrary temperatures.

An error distribution map, indicative of a suspect portion of thetemperature distribution map, is generated by interpolating andextrapolating between the arbitrary temperatures. Typically the errordistribution map comprises a region within a preset isotherm of a mapproduced from the interpolation and extrapolation of the arbitrarytemperatures. The error distribution map is superimposed graphically onthe displayed temperature distribution map, and the superimposed regionacts to indicate a possible problem area of the temperature distributionmap.

System Description

In the following description, like elements in the drawings areidentified by like numerals, and the like elements are differentiated asnecessary by appending a letter to the identifying numeral.

FIG. 1 is a schematic illustration of an invasive medical procedureusing apparatus 12, according to an embodiment of the present invention.The procedure is performed by a medical professional 14, and, by way ofexample, the procedure in the description hereinbelow is assumed tocomprise ablation of a portion of a myocardium 16 of the heart of ahuman patient 18. However, it will be understood that embodiments of thepresent invention are not just applicable to this specific procedure,and may include substantially any procedure on biological tissue.

In order to perform the ablation, professional 14 inserts a probe 20into a lumen of the patient, so that a distal end 22 of the probe entersthe heart of the patient. Distal end 22 comprises electrodes 24 mountedon the outside of the distal end, the electrodes contacting respectivelocations of the myocardium. Probe 20 has a proximal end 28. Distal end22 of the probe is described in more detail below with reference toFIGS. 2A, 2B and 2C.

Apparatus 12 is controlled by a system processor 46, which is located inan operating console 48 of the apparatus. Console 48 comprises controls49 which are used by professional 14 to communicate with the processor.During the procedure, processor 46 typically tracks a location and anorientation of distal end 22 of the probe, using any method known in theart. For example, processor 46 may use a magnetic tracking method,wherein magnetic transmitters external to patient 18 generate signals incoils positioned in the distal end. The Carto® system produced byBiosense Webster, of Diamond Bar, Calif., uses such a tracking method.

The software for processor 46 may be downloaded to the processor inelectronic form, over a network, for example. Alternatively oradditionally, the software may be provided on non-transitory tangiblemedia, such as optical, magnetic, or electronic storage media. The trackof distal end 22 is typically displayed on a three-dimensionalrepresentation 60 of the heart of patient 18 on a screen 62.

In order to operate apparatus 12, processor 46 communicates with amemory 50, which has a number of modules used by the processor tooperate the apparatus. Thus, memory 50 comprises a temperature module52, an ablation module 54, and an interpolation/extrapolation module 56,the functions of which are described below. Memory 50 typicallycomprises other modules, such as a force module for measuring the forceon end 22, a tracking module for operating the tracking method used byprocessor 46, and an irrigation module allowing the processor to controlirrigation provided for distal end 22. For simplicity, such othermodules, which may comprise hardware as well as software elements, arenot illustrated in FIG. 1.

Processor 46 uses results of measurements of temperature acquired bymodule 52 to display on screen 62 a temperature distribution map 63and/or a temperature distribution map 64. Maps 63 and 64 are describedin more detail below.

FIGS. 2A, 2B, and 2C schematically illustrate distal end 22 of probe 20,according to an embodiment of the present invention. FIG. 2A is asectional view along the length of the probe, FIG. 2B is across-sectional view along a cut IIB-IIB that is marked in FIG. 2A, andFIG. 2C is a perspective view of a section of the distal end. Aninsertion tube 70 extends along the length of the probe and is connectedat the termination of its distal end to a conductive cap electrode 24A,which is assumed herein to be used for ablation. FIG. 2C is a schematicperspective view of cap electrode 24A. Cap electrode 24A has anapproximately plane conducting surface 84 at its distal end and asubstantially circular edge 86 at its proximal end. Conductive capelectrode 24A is herein also termed the ablation electrode. Proximal toablation electrode 24A there are typically other electrodes such as anelectrode 24B. Typically, insertion tube 70 comprises a flexible,biocompatible polymer, while electrodes 24A, 24B comprise abiocompatible metal, such as gold or platinum, for example. Ablationelectrode 24A is typically perforated by an array of irrigationapertures 72.

An electrical conductor 74 conveys radio-frequency (RF) electricalenergy from ablation module 54 (FIG. 1), through insertion tube 70, toelectrode 24A, and thus energizes the electrode to ablate myocardialtissue with which the electrode is in contact. Module 54 controls thelevel of RF power dissipated via electrode 24A. During the ablationprocedure, cooling fluid flowing out through apertures 72 may irrigatethe tissue under treatment.

Temperature sensors 78 are mounted within conductive cap electrode 24Aat locations that are arrayed around the distal tip of the probe, bothaxially and circumferentially. In this example, cap 24A contains sixsensors, with one group of three sensors in a distal location, close tothe tip, and another group of three sensors in a slightly more proximallocation. This distribution is shown only by way of example, however,and greater or smaller numbers of sensors may be mounted in any suitablelocations within the cap. Sensors 78 may comprise thermocouples,thermistors, or any other suitable type of miniature temperature sensor.Sensors 78 are connected by leads (not shown in the diagram) runningthrough the length of insertion tube 70 to provide temperature signalsto temperature module 52.

In a disclosed embodiment cap 24A comprises a side wall 73 that isrelatively thick, on the order of 0.5 mm thick, in order to provide thedesired thermal insulation between temperature sensors 78 and thecooling fluid inside a central cavity 75 of the tip. The cooling fluidexits cavity 75 through apertures 72. Sensors 78 are mounted on rods 77,which are fitted into longitudinal bores 79 in side wall 73. Rods 77 maycomprise a suitable plastic material, such as polyimide, and may be heldin place at their distal ends by a suitable glue 81, such as epoxy. U.S.patent application Ser. No. 13/716,578, which is incorporated herein byreference, describes a catheter having temperature sensors mounted in asimilar configuration to that described above. The arrangement describedabove provides an array of six sensors 78, but other arrangements, andother numbers of sensors, will be apparent to those having ordinaryskill in the art, and all such arrangements and numbers are includedwithin the scope of the present invention.

In the description herein, distal end 22 is assumed to define a set ofxyz orthogonal axes, where an axis 92 of the distal end corresponds tothe z axis of the set. For simplicity and by way of example, the y axisis assumed to be in the plane of the paper, the xy plane is hereinassumed to correspond to the plane defined by circle 86, and the originof the xyz axes is assumed to be the center of the circle.

Typically, distal end 22 contains other functional components, which areoutside the scope of the present disclosure and are therefore omittedfor the sake of simplicity. For example, the distal end of the probe maycontain steering wires, as well as sensors of other types, such as aposition sensor and a force sensor. Probes containing components ofthese kinds are described, for example, in U.S. Patent Applications2009/0306650 and 2011/0130648, which are incorporated herein byreference.

FIGS. 3A and 3B are schematic diagrams illustrating, in differentpresentations, the three-dimensional (3D) spatial distribution oftemperature in the vicinity of distal end 22, according to an embodimentof the present invention. FIG. 3A illustrates the spatial distributionas 3D map 63, and FIG. 3B illustrates the spatial distribution astwo-dimensional (2D) map 64. Using measurements provided by temperaturesensors 78, as well as knowledge of the locations of the sensors withrespect to each other and with respect to the xyz axes of distal end 22,processor 46 uses temperature module 52 to generate a 3D spatialdistribution of the temperatures of the external surface of electrode24A. The spatial distribution may be presented on screen 62 as 3D map63. Alternatively or additionally, the processor may project the 3Dspatial distribution to a 2D graphical representation of thedistribution, corresponding to 2D map 64. The processor may presenteither or both maps on screen 62. Both maps are assumed to be drawn withrespect to the xyz axes defined above for distal end 22.

The projection from a 3D distribution to a 2D distribution may be by anymethod known in the projection arts. The calculation of thedistribution, from measurements of sensors 78 and from knowledge of thesensor positions, may use any method of interpolation and extrapolationfrom the measurements that is known in the art. Suitable methods are theInverse Distance Weighting method, and the Gaussian process regressionor Kriging method. In an embodiment of the present inventioninterpolation/extrapolation module 56 (FIG. 1) comprises at least onesuch method, and the module is accessed by processor 46 as required.

3D map 63 is a perspective map, and an edge 99 of the map corresponds toedge 86 of electrode 24A. 2D map 64 is drawn as a circular map on screen62, a bounding circle 100 of the map corresponding with edge 86 ofelectrode 24A. For map 64, x and y axes are shown in FIG. 3B, the axescorresponding to the axes defined above for distal end 22 and beingassumed, by way of example, to be parallel to the edges of screen 62.The axes for either map may be displayed on screen 62, and indicationsof other elements of the distal end, such as the locations of sensors78, may be shown on the screen to assist professional 14 in relating theorientation of the maps to the orientation of the distal end.

3D map 63 and 2D map 64 are typically color maps showing the differenttemperatures of the external surface of electrode 24A, and a legend 104(FIG. 3B) may be displayed with the maps showing values of thetemperatures for the different colors. It will be understood that in themaps any specific color is typically enclosed by isothermal lines, orisotherms, which are usually not shown in the map. (In the figuresdifferent colors are schematically illustrated by different shadings ordifferent gray scales.) In some embodiments the numerical valuesmeasured by each of sensors 78 may also be displayed on map 63 and/ormap 64. For simplicity, the display of such numerical values is notillustrated in FIGS. 3A and 3B.

In a disclosed embodiment, prior to interpolation and extrapolation, thetemperatures measured by sensors 78 are normalized. An expected coldesttemperature measured by the sensors may be set as 0, and an expectedhottest temperature measured by the sensors may be set as 1. Theexpected coldest temperature may be the lowest value displayed on legend104, and the expected hottest temperature may be the highest valuedisplayed on the legend. By way of example the expected coldesttemperature may be 20° C. and the expected hottest temperature may be40° C., as is illustrated in FIG. 3B. It will be understood that, in thecase of map 63 or map 64 being a color map, while the map may beprepared using normalized values for the temperatures, the colors of themap indicate non-normalized temperature values.

FIG. 4 is a flowchart of steps followed by processor 46 in operatingapparatus 12, according to an embodiment of the present invention. In aninitial step 120 processor 46 acquires signals from sensors 78, and usestemperature module 52 to convert the acquired signal levels totemperatures. By way of example, in the following description, exceptwhere otherwise stated, processor 46 is assumed not to have normalizedthe temperature values produced by module 52 as described above. Inaddition, module 56 is assumed to store the Inverse Distance Weightingmethod. However, those having ordinary skill in the art will be able toadapt the description, mutatis mutandis, for embodiments where thetemperatures are normalized, and/or where a different method ofinterpolation and extrapolation is stored in module 56.

In a first interpolation and display step 122, the processor accessesinterpolation/extrapolation module 56, and applies the method stored inthe module to interpolate and extrapolate between the temperatures ofsensors 78, according to the spatial positions of the sensors. Themethod produces a 3D spatial distribution of temperatures. The processormay present the spatial distribution as a 3D temperature distributionmap on screen 62, and/or project the 3D spatial distribution to a 2Dtemperature distribution map which is displayed on the screen. FIGS. 3Aand 3B illustrate typical 3D and 2D maps produced in step 122.

In a malfunctioning sensor step 124, the processor determines that oneof sensors 78 is malfunctioning. The determination is typically made bythe processor registering that the sensor gives a temperature readingoutside a preset acceptable range of temperatures. The malfunction maybe caused, for example, by a broken lead to or from the sensor, by ashort-circuit in one of the leads, or by failure of the sensor itself.In some embodiments professional 14 suspects that one of sensors 78 ismalfunctioning, and uses controls 49 to inform the processor of thesuspect sensor, whereupon the processor proceeds as described below instep 126.

In an assignment step 126, the processor assigns the malfunctioningsensor a first arbitrary temperature, and the remaining, correctlyoperating sensors, a second arbitrary temperature. In one embodiment thefirst arbitrary temperature is set at 0° C., and the second arbitrarytemperature is set at 100° C. If the processor is using a normalizedsystem, then these settings are equivalent to the first arbitrarynormalized temperature being set as 0, and the second arbitrarynormalized temperature being set as 1.

In a second interpolation and display step 128, the processor accessesinterpolation/extrapolation module 56. The processor typically appliesthe method stored in the module to interpolate and extrapolate betweenthe first arbitrary temperature of the malfunctioning sensor and thesecond arbitrary temperature of the correctly operating sensors,according to the spatial positions of the sensors. Alternatively, theprocessor may use a different method to perform the interpolation andextrapolation. The interpolation and extrapolation produces a 3D spatialdistribution of temperatures, based on the arbitrary temperatures, andherein termed a 3D spatial arbitrary temperature distribution.

The interpolation producing the 3D spatial arbitrary temperaturedistribution typically generates a continuous distribution oftemperatures between the first arbitrary and second arbitrarytemperatures. (The extrapolation typically produces a continuousdistribution of temperatures outside the two arbitrary temperatures.) Inan embodiment of the present invention, a section of the 3D arbitrarytemperature distribution that is suspected to have erroneous results isselected, and is herein termed an error region.

In a disclosed embodiment the selected section comprises a portion ofthe 3D spatial arbitrary temperature distribution that is containedwithin a preset isotherm of the distribution. A 2D or 3D errordistribution map may be used to illustrate areas, in the respective 2Dor 3D map produced in step 122, corresponding to the error region.

Thus, referring back to 2D arbitrary temperature distribution map 64(FIG. 3B), the 2D selected section is a 2D area in the map that may bedisplayed on screen 62, and an expression for the 2D selected section isgiven by expression (1):

{(x,y)|(x ² +y ²)≤r² and T≥K}  (1)

where r is the radius of bounding circle 100,

T is the temperature of a point (x,y) within the bounding circle, and

K is a value of the preset isotherm.

It will be understood from expression (1) that the selected 2D section,the 2D error distribution map of the error region, is a subset of map64. Similarly, in the case of the 3D arbitrary temperature distribution,the 3D selected section—the 3D error distribution map of the errorregion—is a subset of map 63.

For the example above where the first arbitrary temperature is 0° C.,and the second arbitrary temperature is 100° C., the isotherm may, byway of example, be preset at 60° C., so that in expression (1) K=60. Inthe case where temperatures are normalized, then this example isequivalent to the first and second arbitrary normalized temperaturesrespectively being 0 and 1, and K being 0.6.

FIGS. 5A and 5B respectively schematically illustrate a 3D errordistribution map 142 and a 2D error distribution map 152, according toan embodiment of the present invention. Maps 142 and 152 are producedusing the exemplary arbitrary temperature values given above, i.e.,where the first arbitrary temperature is 0° C., and the second arbitrarytemperature is 100° C. 3D map 142 is drawn using the same perspective asmap 63 and illustrates edge 99. 2D map 152 is drawn within boundingcircle 100. An isotherm 144 of 3D map 142, corresponding to the edge ofthe error region, is by way of example preset at T=60° C. An isotherm154 of 2D map 152 is also set at T=60° C. Thus, K=60 in expression (1).

Returning to the flowchart of FIG. 4, in a final step 130, the processoroverlays, i.e., superimposes graphically, the error distribution mapgenerated in step 128 on the temperature distribution map of step 122.

FIGS. 6A and 6B schematically illustrate an implementation of theflowchart of FIG. 4, according to an embodiment of the presentinvention. For a two-dimensional representation, the flowchart isassumed to be applied to 2D temperature distribution map 64 of FIG. 3B,and is also assumed to generate 2D error distribution map 152 of FIG.5B, so that line 154 represents isotherm T=K=60, and a region, withinthe isotherm, represents the 2D error distribution map. For athree-dimensional representation, the flowchart is assumed to be appliedto 3D temperature distribution map 63 of FIG. 3A, and is also assumed togenerate error distribution map 142 of FIG. 5A, so that line 144represents isotherm T=60, and a region, within the isotherm, representsthe 3D error distribution map.

In the implementation of the flowchart, i.e., when step 130 hascompleted, error distribution maps 142 and 152 are implemented to bevisually different and distinct from the elements of maps 63 and 64, andin one embodiment maps 142 and 152 are presented on screen 62 as blackelements within a white background. However, the error distributionmaps, generated by the flowchart, may be presented on screen 62 by anyconvenient method that differentiates them visually from theirunderlying temperature distribution maps. In one embodiment maps 142 and152 are implemented to be at least partially transparent, so thattemperature values of maps 63 and 64, underlying maps 142 and 152 and sobeing suspect, are visible. In an alternative embodiment, maps 142 and152 comprise isotherms, of values greater than the bounding isothermcorresponding to lines 144 and 154, which are drawn as at leastpartially transparent black lines. The thickness of the normalizedisotherm lines may increase as the value of the isotherm increases.

The description above provides one example of how an error distributionmap may be superimposed on another distribution map, so as to provide anindication of a suspect portion of the other map. It will be understoodthat the methods described above may be applied, mutatis mutandis, toother systems where there may be a suspect portion in a distributionmap.

For example, prior to the ablation described above (with reference toFIG. 1) professional 14 may use processor 46 to prepare a 3D localactivation time (LAT) distribution map of the heart. Such a 3Ddistribution map is usually generated from LAT measurements made byelectrodes 24 acquiring signals from the heart at known points, andinterpolating and extrapolating between these points, typically usingone of the methods referenced above.

Processor 46 may be used to analyze data used to generate the graph, andmay determine that an area of the graph may be suspect, typically byfinding that there are insufficient points for valid interpolation orextrapolation. In this case, to generate a 3D error distribution map oneor more signals from points in proximity to the area may be assigned afirst arbitrary metric value, and the remaining signals may be assigneda second arbitrary metric value. The values may be normalized, so thatthe first normalized value is set at 0, and the second normalized valueis set at 1. Using normalized or non-normalized arbitrary values,processor 46 produces a 3D error distribution map, generally asdescribed above. The processor then superimposes the 3D error map on the3D LAT distribution map.

As an alternative example, one or more of the signals acquired for theLAT measurements may conflict with other measurements. The conflictingmeasurements are typically from one or more points in proximity topoints where the LAT measurement is correct. For example, there may be alarger than acceptable LAT difference between the points generating theconflict and points in proximity to these points. To generate a 3D errordistribution map the one or more signals giving conflicting LAT valuesmay be assigned a first arbitrary metric value, and the remainingsignals may be assigned a second arbitrary metric value. The values maybe normalized, so that the first normalized value is set at 0, and thesecond normalized value is set at 1.

As described above, using normalized or non-normalized arbitrary values,processor produces a 3D error distribution map. The processor thensuperimposes the 3D error map on the 3D LAT distribution map.

It will be appreciated that there are other cases where a 2D or 3D errordistribution map may be determined and respectively overlaid on a 2D or3D distribution map of a metric, using the methods described above, andall such cases are assumed to be comprised within the scope of thepresent invention.

It will thus be appreciated that the embodiments described above arecited by way of example, and that the present invention is not limitedto what has been particularly shown and described hereinabove. Rather,the scope of the present invention includes both combinations andsubcombinations of the various features described hereinabove, as wellas variations and modifications thereof which would occur to personsskilled in the art upon reading the foregoing description and which arenot disclosed in the prior art.

We claim:
 1. Apparatus, comprising: a probe, in contact with abiological tissue and comprising a plurality of thermal sensors; and aprocessor configured to: acquire signals, indicative of temperatures atrespective spatial locations in the biological tissue, from theplurality of thermal sensors, perform a first interpolation or a firstextrapolation between temperatures determined from the signals based onthe spatial locations of the thermal sensors so as to produce atemperature spatial distribution map, display the temperature spatialdistribution map on a screen, determine that there is at least onemalfunctioning thermal sensor of the plurality of thermal sensors, andthat remaining thermal sensors of the plurality of thermal sensors arecorrectly operating thermal sensors, assign the at least onemalfunctioning thermal sensor a first arbitrary temperature and each ofthe correctly operating thermal sensors a second arbitrary temperature,in the case of performing the first interpolation, perform a secondinterpolation between the first arbitrary temperature and the secondarbitrary temperatures based on the spatial locations of the thermalsensors so as to produce a spatial distribution of arbitrarytemperatures, in the case of performing the first extrapolation, performa second extrapolation between the first arbitrary temperature and thesecond arbitrary temperatures based on the spatial locations of thethermal sensors so as to produce a spatial distribution of arbitrarytemperatures, select a section of the spatial distribution of arbitrarytemperatures as having erroneous results to produce an errordistribution map, and superimpose graphically the error distribution mapon the displayed temperature distribution map displayed on the screen.2. The apparatus according to claim 1, wherein the spatial distributionof arbitrary temperatures is a continuous distribution of temperatures.3. The apparatus according to claim 2, wherein the second interpolationproduces the continuous distribution of temperatures between the firstand second arbitrary temperatures.
 4. The apparatus according to claim2, wherein the second extrapolation produces the continuous distributionof temperatures outside the first and second arbitrary temperatures. 5.The apparatus according to claim 1, wherein the error distribution mapcomprises a region enclosed by an isotherm.
 6. The apparatus accordingto claim 1, wherein the error distribution map is produced as a twodimensional map and the temperature distribution map is produced as atwo dimensional map.
 7. The apparatus according to claim 1, wherein theerror distribution map is produced as a three dimensional map and thetemperature distribution map is produced as a three dimensional map. 8.The apparatus according to claim 1, wherein the error distribution mapis at least partially transparent so that a region of the temperaturedistribution map underlying the error distribution map is visible. 9.The apparatus according to claim 1, wherein the error distribution mapis differentiated visually from the temperature distribution map. 10.The apparatus according to claim 1, wherein determining that there is atleast one malfunctioning thermal sensor comprises registering that atemperature indicated by at least one of the plurality of thermalsensors is outside a preset acceptable range of temperatures.
 11. Acomputer implemented method, comprising: acquiring signals, indicativeof temperatures at respective spatial locations in the biologicaltissue, from a plurality of thermal sensors, performing a firstinterpolation or a first extrapolation between temperatures determinedfrom the signals based on the spatial locations of the thermal sensorsso as to produce a temperature spatial distribution map, displaying thetemperature spatial distribution map on a screen, determining that thereis at least one malfunctioning thermal sensor of the plurality ofthermal sensors, and that remaining thermal sensors of the plurality ofthermal sensors are correctly operating thermal sensors, assigning theat least one malfunctioning thermal sensor a first arbitrary temperatureand each of the correctly operating thermal sensors a second arbitrarytemperature, in the case of performing the first interpolation,performing a second interpolation between the first arbitrarytemperature and the second arbitrary temperatures based on the spatiallocations of the thermal sensors so as to produce a spatial distributionof arbitrary temperatures, in the case of performing the firstextrapolation, performing a second extrapolation between the firstarbitrary temperature and the second arbitrary temperatures based on thespatial locations of the thermal sensors so as to produce a spatialdistribution of arbitrary temperatures, selecting a section of thespatial distribution of arbitrary temperatures as having erroneousresults to produce an error distribution map, and superimposinggraphically the error distribution map on the displayed temperaturedistribution map displayed on the screen.
 12. The method according toclaim 11, wherein the spatial distribution of arbitrary temperatures isa continuous distribution of temperatures.
 13. The method according toclaim 12, wherein the second interpolation produces the continuousdistribution of temperatures between the first and second arbitrarytemperatures.
 14. The method according to claim 12, wherein the secondextrapolation produces the continuous distribution of temperaturesoutside the first and second arbitrary temperatures.
 15. The methodaccording to claim 11, wherein the error distribution map comprises aregion enclosed by an isotherm.
 16. The method according to claim 11,wherein the error distribution map is produced as a two dimensional mapand the temperature distribution map is produced as a two dimensionalmap.
 17. The method according to claim 11, wherein the errordistribution map is produced as a three dimensional map and thetemperature distribution map is produced as a three dimensional map. 18.The method according to claim 11, wherein the error distribution map isat least partially transparent so that a region of the temperaturedistribution map underlying the error distribution map is visible. 19.The method according to claim 11, wherein the error distribution map isdifferentiated visually from the temperature distribution map.
 20. Themethod according to claim 11, wherein determining that there is at leastone malfunctioning thermal sensor comprises registering that atemperature indicated by at least one of the plurality of thermalsensors is outside a preset acceptable range of temperatures.